Transactions on Large-Scale Data- and Knowledge-Centered Systems LI: Special Issue on Data Management - Principles, Technologies and Applications

✍ Scribed by Abdelkader Hameurlain, A. Min Tjoa, Esther Pacitti, Zoltan Miklos

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 145
• Series: Lecture Notes in Computer Science, 13410
• Category: Library

✦ Synopsis

The LNCS journal Transactions on Large-Scale Data and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.

This, the 51st issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains five fully revised selected regular papers. Topics covered include data anonyomaly detection, schema generation, optimizing data coverage,  and digital preservation with synthetic DNA.

✦ Table of Contents

Preface
Organization
Contents
Threats Modeling and Anomaly Detection in the Behaviour of a System - A Review of Some Approaches
1 Introduction
2 Background and Related Work
2.1 Threats and Attacks in Cybersecurity
2.2 Threat Modelling
2.3 Intrusion Detection Systems - IDS
2.4 Machine Learning Threats and Vulnerabilities
2.5 Detection Tools
3 Anomaly Detection for Cybersecurity
3.1 General Concepts
3.2 Characteristics of an Anomaly Detection Problem
3.3 Anomaly Detection Techniques
4 Experiments
4.1 Dataset Description
4.2 Data Preparation
5 Results and Comparative Study
5.1 Scenario 1
5.2 Scenario 2
5.3 Scenario 3
5.4 Discussion
6 Conclusion and Future Work
References
Incremental Schema Generation for Large and Evolving RDF Sources
1 Introduction
2 Problem Statement
3 Schema Evolution After Entity Insertions
3.1 Data Distribution Principle for Neighborhood Computation
3.2 Computing the Neighborhood of the New Entities
3.3 Generating the New Schema
4 Schema Evolution After Entity Deletions
4.1 Data Distribution
4.2 Updating the Neighborhood of the Impacted Entities
4.3 Generating the New Schema
5 Experimental Evaluations
5.1 Experimental Setup
5.2 Evaluating Scalability When Dealing with Insertions
5.3 Evaluating Scalability When Dealing with Deletions
6 Related Work
7 Conclusion
References
Optimizing Data Coverage and Significance in Multiple Hypothesis Testing on User Groups
1 Introduction
2 Related Work
3 The GroupTest Framework
3.1 Motivating Examples
3.2 Groups
3.3 Group Testing
3.4 Our Problems
4 Algorithms
4.1 Algorithm VAL_C
4.2 Algorithm COVER_G
4.3 Algorithm COVER_
5 Experiments
5.1 Addressing Information Needs
5.2 Experimental Setup
5.3 ValMin Results
5.4 CovMax Results
6 Conclusion and Future Work
References
Efficiently Identifying Disguised Missing Values in Heterogeneous, Text-Rich Data
1 Introduction
2 Related Work
3 Motivating Example
4 Detecting DMVs with Entity Profiles
5 DMV Detection Through Embedding and Classification
5.1 Textual Data Representation
5.2 Classification Model
5.3 Placing Our DMV Detection Methods in Context
6 Integrating our DMV Detection Methods within ConnectionLens
6.1 ConnectionLens Architecture
6.2 Integrating Our DMV Detection Method Within ConnectionLens
7 Experimental Evaluation
7.1 Datasets
7.2 Settings
7.3 DMV Detection Through FAHES
7.4 DMV Detection Through Entity Profiles
7.5 DMV Detection Through Embedding and Classification
7.6 Comparison on Manually Labeled Data
7.7 DMV Detection Integrated in ConnectionLens
8 Conclusion
References
Digital Preservation with Synthetic DNA
1 Introduction
2 Context and Background
2.1 Danish National Archive Use Case
2.2 DNA Storage Challenges
3 Design
3.1 Overcoming Format Obsolescence with SIARD-DK
3.2 DNA Data Storage Pipeline
4 Evaluation
4.1 Experimental Setup
4.2 Benchmark with Sequence Alignment
4.3 End-to-End Decoding Results
5 Conclusion and Future Work
References
Author Index